• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.174-179
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• 2003

Through the simultaneous localization and map building (SLAM) technique, a robot can create maps about its unknown environment while it continuously localizes its position. Grid maps and feature maps have been widely used for SLAM together with application of probability methods and POMDP (partially observed Markov decision process). But this approach based on grid maps suffers from enormous computational burden. Topological maps, however, have drawn more attention these days because they are compact, provide natural interfaces, and are easily applicable to path planning in comparison with grid maps. Some topological SLAM techniques like GVG (generalized Voronoi diagram) were introduced, but it enables the robot to decide only whether the current position is part of GVG branch or not in the GVG algorithm. In this paper, therefore, to overcome these problems, we present a method for updating a global topological map from the local topological maps. These local topological maps are created through a labeled Voronoi diagram algorithm from the local grid map built based on the sensor information at the current robot position. And the nodes of a local topological map can be utilized as the features of the environment because it is robust in light of visibility problem. The geometric information of the feature is applied to the extended Kalman filter and the SLAM in the indoor environment is accomplished. A series of simulations have been conducted using a two-wheeled mobile robot equipped with a laser scanner. It is shown that the proposed scheme can be applied relatively well.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.2
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• pp.180-187
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• 2010

In this paper, a global path generation method is suggested using multiple grid maps connected with the mission type of unmanned combat vehicle(UCV). In order to carry out a mission for UCV, it is essential to find a global path which is coincident with the characteristics of the mission. This can be done by considering various combat circumstances represented as grid maps such as velocity map, threat map and communication map. Cost functions of multiple grid maps are linearly combined and normalized to them simultaneously for the path generation. The proposed method is realized using $A^*$, a well known search algorithm, and cost functions are normalized in the ratio of the traverse time which is one of critical information should be provided with the operators using the velocity map. By the experiments, it is checked found global paths match with the mission type by reflecting input data of grid maps properly and the computation time is short enough to regenerate paths in real time as combat circumstances change.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.85-92
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• 2015

As computer game maps get more elaborate, path-finding by using $A^*$ algorithm in grid-based game maps becomes bottlenecks of the overall game performance. It is because the search space becomes large as the number of nodes increases with detailed representation in cells. In this paper we propose an efficient pathfinding method in which the computer game maps in a regular grid is converted into the polygon-based representation of the list of vertices and then the visibility information about vertices of polygons can be utilized. The conversion to the polygon-based map does not give any effect to the real-time query process because it is preprocessed offline. The number of visited nodes during search can be reduced dramatically by designing heuristics using visibility information of vertices that make the accuracy of the estimation enhanced. Through simulations, we show that the proposed methods reduce the search space and the search time effectively while maintaining the advantages of the grid-based method.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.2
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• pp.101-107
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• 2014

Mobile robots use an environment map of its workspace to complete the surveillance task. However grid-based maps that are commonly used map format for mobile robot navigation use a large size of memory for accurate representation of environment. In this reason, grid-based maps are not suitable for path planning of mobile robots using embedded board. In this paper, we present the path planning algorithm that produce a secure path rapidly. The proposed approach utilizes a hybrid map that uses less memory than grid map and has same efficiency of a topological map. Experimental results show that the fast path planning uses only 1.5% of the time that a grid map based path planning requires. And the results show a secure path for mobile robot.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.583-589
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• 2013

In this paper, we proposed a system that efficiently provides support maps which includes the grid based terrain analysis information. To do this, we use the FDB which is defined as a GIS database that contains features with attributes attached to the features. The FDB is composed of a number of features and feature classes. In order to create support maps, it is necessary to classify feature classes that are associated with each support map and to search them in a grid map. The proposed system use a ontology model to classify semantically feature classes and the quad-tree data structure to find them in a grid map quickly. Therefore, our system is expected to be utilized for global path planning of UGV. In this paper, we show the possibility through an experimental implementation.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.247-254
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• 2011

This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.492-497
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• 2002

Map building is the process of modeling the robot's environment. The map is usually built based on a grid-based or topological approach, which has its own merits and demerits. These two methods, therefore, can be integrated to provide a better way of map building, which compensates for each other's drawbacks. In this paper, a method of building the topological map based on the occupancy grid map through a Voronoi diagram is presented and verified by various simulations. This Voronoi diagram is made by using a labeled Voronoi diagram scheme which is suitable for the occupancy grid maps. It is shown that the Proposed method is efficient and simple fur building a topological map. The simple path-planning problem is simulated and experimented verify validity of the proposed approach.

• Journal of Korea Water Resources Association
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• v.31 no.3
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• pp.303-308
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• 1998

A grid-based KInematic were STOrm Runoff Model (KIMSTORM) with predicts temporal and spatial distributions of saturalted orerland flow, subsurface flow and stream flow in a watershed was developed. The model adopts the single overland flowpath algorithm and simulates surface and/or subsurface water depth at each grid element by using grid-based water balance of hydrologic components. The model which is programmed by C-language uses ASCII-formatted map data supported by the irregular gridded map of the GRASS(Geographic Resources Analysis Support System) GIS and generates the spatial distribution maps of discharge, flow depth and soil moisture within the watershed.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.14-22
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• 2014

An autonomous vehicle requires a technology of generating maps by recognizing surrounding environment. The recognition of the vehicle's environment can be achieved by using distance information from a 2D laser scanner and color information from a camera. Such sensor information is used to generate 2D or 3D maps. A 2D map is used mostly for generating routs, because it contains information only about a section. In contrast, a 3D map involves height values also, and therefore can be used not only for generating routs but also for finding out vehicle accessible space. Nevertheless, an autonomous vehicle using 3D maps has difficulty in recognizing environment in real time. Accordingly, this paper proposes the technology for generating 2D maps that guarantee real-time recognition. The proposed technology uses only the color information obtained by removing height values from 3D maps generated based on the fusion of 2D laser scanner and camera data.

• Water Engineering Research
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• v.1 no.4
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• pp.321-330
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• 2000

The grid-based KIneMatic wave STOrm Runoff Model(Kim, 1998; Kim, et al., 1998) which predicts temporal variation and spatial distribution of overland flow, subsurface flow and stream flow was evaluated at two watersheds. This model adopts the single overland flowpath algorithm and simulates surface and/or subsurface water depth at each cell by using water balance of hydrologic components. The model programmed by C-language uses ASCII-formatted map data supported by the irregular gridded map of the GRASS(Geographic Resources Analysis Support System) GIS and generates the spatial distribution maps of discharge, flow depth and soil moisture of the watershed.